4.8 Article

The correlation between the physicochemical properties and enzymatic hydrolyzability of hydrothermal pretreated wheat straw: A quantitative analysis

期刊

BIORESOURCE TECHNOLOGY
卷 359, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.biortech.2022.127475

关键词

Lignocellulosic biomass; Hydrothermal pretreatment; Enzymatic hydrolysis; Correlation analysis; Principal component analysis

资金

  1. National Natural Science Foundation of China [51836001]
  2. Innovative Research Group Project of Na-tional Natural Science Foundation of China [52021004]
  3. Na-tional Natural Science Funds for Excellent Young Scholar [52022015]
  4. Natural Science Foundation of Chongqing [cstc2021ycjh-bgzxm0342, cstc2021ycjh-bgzxm0200]

向作者/读者索取更多资源

This study investigated the relationship between the physicochemical properties and enzymatic hydrolyzability of hydrothermal pretreated lignocellulose through correlation analysis and principal component analysis. The results showed that cellulose content was the major factor affecting carbohydrate conversion, and the initial hydrolysis rate and carbohydrate conversion could be well predicted using principal component analysis.
Hydrothermal pretreatment with diluted acid or alkali can disrupt the compact structure of wheat straw at a moderate temperature for efficient enzymatic saccharification. However, the quantitative analysis between the physicochemical properties and enzymatic hydrolyzability of hydrothermal pretreated lignocellulose was rarely investigated, which hindered the development of model-based applications for process design and control. Herein, correlation analysis (CA) and principal component analysis (PCA) were conducted to elucidate the dominant factors affecting the enzymatic hydrolyzability and quantitative relationship between them. CA results suggested the major positive factor affecting carbohydrate conversion was cellulose content (r = 0.86). Through logarithmic processing and linear combination, these intercorrelated factors were successfully converted into two newly uncorrelated variables named the first principal component (PC1) and the second principal component (PC2). The initial hydrolysis rate and carbohydrate conversion can be well predicted by PC1 and PC2 scores through multiple linear regression with a high R-squared (0.91 and 0.80).

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